Yin Junjun, Brooks Matthew, Wang Donghui, Chi Guangqing
Population Research Institute and Social Science Research Institute, The Pennsylvania State University, University Park, PA 16802, USA.
Department of Sociology, Florida State University, Tallahassee, FL 32306, USA.
Digit Geogr Soc. 2025 Jun;8. doi: 10.1016/j.diggeo.2024.100110. Epub 2024 Dec 22.
The profound impacts of climate change have spurred global concerns. Yet, public perceptions of this issue exhibit significant variations rooted in local contexts. This study investigates public perceptions of climate change in Alaska on Twitter and explores their connections with local socioeconomic and environmental factors. Using geo-located tweets from 2014 to 2017, we identified a collection of climate-related tweets using a deep learning framework. Employing lexicon-based sentiment analysis, we quantified the sentiments with positive and negative scores, further enriched by extracting eight core emotions expressed in each tweet. Furthermore, we applied regression models to assess the influence of regional socioeconomic and environmental attributes on climate-related sentiments at the census tract level. Our findings reveal an overall upward trajectory of Alaska's Twitter-expressed climate change sentiments over time, particularly during the summer months. Insights into the interplay between local demographics and environmental features and climate change perceptions include: (1) Census tracts with higher Native Alaskan or American Indian populations tend to express more negative sentiments, (2) the inclusion of road density stands out as a significant factor, suggesting that climate change is seen/discussed more in areas with more dense-built infrastructure, and (3) the presence of mixed emotions exhibits a profound connection with climate change sentiments-i.e., emotions of disgust and surprise are inversely related, whereas sadness and trust demonstrate positive associations. These outcomes underscore an evolving situation awareness of climate change among individuals, emphasizing the need to consider local factors in understanding public perceptions of this global issue.
气候变化的深远影响引发了全球关注。然而,公众对这一问题的认知因当地情况而存在显著差异。本研究调查了阿拉斯加民众在推特上对气候变化的看法,并探讨了这些看法与当地社会经济和环境因素之间的联系。利用2014年至2017年带有地理位置信息的推文,我们使用深度学习框架识别出一系列与气候相关的推文。通过基于词典的情感分析,我们用正负面分数对情感进行量化,并通过提取每条推文中表达的八种核心情感进一步丰富分析结果。此外,我们应用回归模型来评估区域社会经济和环境属性对人口普查区层面与气候相关情感的影响。我们的研究结果显示,随着时间推移,阿拉斯加推特上表达的气候变化情感总体呈上升趋势,尤其是在夏季月份。对当地人口结构与环境特征以及气候变化认知之间相互作用的洞察包括:(1)阿拉斯加原住民或美国印第安人口比例较高的人口普查区往往表达出更多负面情绪;(2)道路密度是一个突出的重要因素,这表明在基础设施建设更为密集的地区,气候变化更容易被提及/讨论;(3)混合情感的存在与气候变化情感有着深刻联系——即厌恶和惊讶的情感呈负相关,而悲伤和信任则呈正相关。这些结果强调了个人对气候变化的态势感知在不断演变,突出了在理解公众对这一全球问题的认知时考虑当地因素的必要性。